Nazarov Petr V, Muller Arnaud, Kaoma Tony, Nicot Nathalie, Maximo Cristina, Birembaut Philippe, Tran Nhan L, Dittmar Gunnar, Vallar Laurent
Proteome and Genome Research Unit, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
INSERM UMRS 903, University of Reims Champagne-Ardenne, Reims, France.
BMC Genomics. 2017 Jun 6;18(1):443. doi: 10.1186/s12864-017-3819-y.
RNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study.
Both platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques.
Despite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.
RNA测序(RNA-seq)和微阵列是两种转录组学技术,旨在对转录基因及其异构体进行定量分析。在此,我们将最新的Affymetrix HTA 2.0微阵列与Illumina 2000 RNA-seq进行比较,用于分析患者样本——正常肺上皮组织和肺鳞状细胞癌肿瘤。研究纳入了蛋白质编码mRNA和长链非编码RNA(lncRNA)。
对于蛋白质编码RNA,两个平台的表现同样出色,然而测序数据的随机变异性高于微阵列。与微阵列数据相比,这减少了RNA-seq中差异表达基因和具有预测潜力的基因数量。对这种变异性的分析揭示了短基因和低丰度基因的读数不足;lncRNA作为较短且丰度较低的RNA,尤其容易受到这个问题的影响。通过对可变剪接基因的分析,发现了两个平台之间的一个主要差异。对差异外显子丰度的研究表明,RNA-seq中许多外显子和外显子连接的读数不足,而阵列平台上的检测更稳定。尽管如此,我们鉴定出207个经历可变剪接且两种技术均能一致检测到的基因。
尽管人类转录组阵列和RNA-seq平台之间的基因表达分析结果高度一致,但可变剪接分析产生了不一致的结果。我们得出结论,就可重复性和成本而言,现代微阵列在基因表达的标准分析方面仍可优于测序。